Machines such as, for example, dozers, motor graders, wheel loaders, wheel tractor scrapers, and other types of heavy equipment are used to perform a variety of tasks at a worksite. Autonomously and semi-autonomously controlled machines are capable of operating with little or no human input by relying on information received from various machine systems. For example, based on machine movement input, terrain input, and/or machine operational input, a machine can be controlled to remotely and/or automatically complete a programmed task. By receiving appropriate feedback from each of the different machine systems during performance of the task, continuous adjustments to machine operation can be made that help to ensure precision and safety in completion of the task. In order to do so, however, the information provided by the different machine systems should be accurate and reliable. The position, velocity, and/or distance traveled by the machine are parameters, the accuracy of which may be important for control of the machine and its operation.
Conventional machines typically utilize a navigation or position system to determine various operating parameters, such as position, velocity, pitch rate, yaw rate, and/or roll rate for the machine. Some conventional machines utilize a combination of one or more Global Positioning System (GPS) data, a Distance Measurement Instrument (DMI) and/or odometer measurement data, and/or Inertial Measurement Unit (IMU) data to determine these parameters. Some machines utilize radar sensors, sonar sensors, LIDAR sensors, IR and non-IR cameras, and similar sensors to help guide the machines safely and efficiently in the worksite. In various worksite conditions, different measuring and sensing devices work better than others. Machines utilize combinations of data from these different types of measuring and sensing devices in an attempt to produce robust positioning systems that work in various worksite conditions.
An exemplary system that may be utilized to determine the position of a machine is disclosed in co-pending U.S. patent application Ser. No. 13/721,958 to Friend et al. (“the '958 application”). The system of the '958 application utilizes a perception sensor, such as a LIDAR sensor, to obtain a first estimated position of the machine based on scene data obtained by the perception sensor. The system obtains the first estimated position using a perception-based localization method. The system also obtains a second estimated position of the machine based on a location signal, such as a GPS signal. Based on a comparison of the first estimated position and the second estimated position, the system may estimate the position of the machine.
The positioning system of the present disclosure provides for enhancements to the perception-based localization method of the '958 application, such that the disclosed positioning system may be utilized in additional worksite conditions.